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Preserving key topological and structural features in the synthesis of multilevel electricity networks for modeling of resilience and risk

Abstract:
Given the often-limited availability of real electricity network data, this paper presents methodology for the synthesis of multilevel electricity networks for use in applied network failure and risk analysis. The proposed algorithm is capable of producing networks that preserve a number of important spatial and topological properties of real-world networks including the multilevel structure of subsystems, the geographic distribution of network nodes, the node degree distribution, and the networks spatial connectivity. The algorithm is capable of integrating both synthetic and real data from a range of sources to produce spatially and topologically continuous representations. The flexibility of the algorithm is demonstrated through the synthesis of a regional-scale electricity network. The practicality of the algorithm, in terms of providing new data to conduct applied risk and resilience studies of interdependent infrastructures, is demonstrated through the synthesis of a unique representation of the national integrated electricity network for England and Wales, bridging the transmission, subtransmission, and distribution scales and consisting of more than 160,000 nodes.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1061/(ASCE)IS.1943-555X.0000404

Authors


More by this author
Institution:
University of Oxford
Division:
Social Sciences Division
Department:
SOGE; Environmental Change Institute
Role:
Author
More by this author
Institution:
University of Oxford
Division:
SSD
Department:
SOGE
Sub department:
Environmental Change Institute
Role:
Author
ORCID:
0000-0002-2024-9191
More by this author
Institution:
University of Oxford
Division:
Social Sciences Division
Department:
SOGE; Environmental Change Institute
Role:
Author


Publisher:
American Society of Civil Engineers
Journal:
Journal of Infrastructure Systems More from this journal
Volume:
24
Issue:
1
Pages:
04017043
Publication date:
2017-11-01
Acceptance date:
2017-06-12
DOI:
EISSN:
1943-555X
ISSN:
1076-0342


Keywords:
Pubs id:
pubs:811418
UUID:
uuid:9866f034-1328-444c-8b29-6fd9b6287efb
Local pid:
pubs:811418
Source identifiers:
811418
Deposit date:
2018-03-01

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